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Spread & networksBots & coordinated campaigns
On the Detection of Disinformation Campaign Activity with Network AnalysisState-sponsored disinformation campaigns on Twitter exhibit distinct coordination patterns (shared messages, hashtags, URLs, retweet cascades) that differ from legitimate coordinated activity. The paper proposes using coordination network features—extracted from daily account interactions—to train a binary classifier that detects…
Detection methodsLLMs & generative AI
The Limitations of Stylometry for Detecting Machine-Generated Fake NewsWhile stylometry effectively detects impersonation and provenance, it fails to distinguish between legitimate and malicious uses of language models for generating false content. LMs produce stylistically consistent text regardless of veracity, and adding even a single auto-generated sentence within human-written text evades stylometric…
Bots & coordinated campaignsSpread & networks
Uncovering Coordinated Networks on Social Media: Methods and Case StudiesThis paper proposes a general, unsupervised, network-based methodology to detect coordinated inauthentic behavior on social media. The approach identifies behavioral traces (handle changes, image sharing, hashtag sequences, co-retweets, synchronized actions) and constructs bipartite networks to discover clusters of accounts likely…
Spread & networksPlatforms, policy & society
Exposure to untrustworthy websites in the 2016 US electionUsing combined survey and web-traffic data from the 2016 US presidential election, Guess et al. found that while 44.3% of Americans aged 18+ visited an untrustworthy website during the campaign, actual exposure was highly concentrated among Trump supporters (56.7% of Trump supporters vs. 27.7% of Clinton supporters). Facebook played a…
Spread & networksPlatforms, policy & society
Assessing the risks of 'infodemics' in response to COVID-19 epidemicsAnalysis of 112+ million geolocated Twitter messages about COVID-19 (January–March 2020) across 64 languages and countries. Develops an infodemic risk index (IRI) measuring exposure to unreliable news; demonstrates that waves of unreliable information precede pandemic waves, providing early-warning signals for policy intervention.
Fact-checking & verificationPlatforms, policy & society
Types, Sources, and Claims of COVID-19 MisinformationSystematic analysis of 225 fact-checked COVID-19 misinformation pieces reveals that most false content reconfigures existing information (59%) rather than fabricating entirely new claims. Public authorities are cited in 39% of misinformation, yet top-down claims from politicians and celebrities account for only 20% of volume but drive…
LLMs & generative AIPlatforms, policy & society
Language Models are Few-Shot LearnersThis landmark paper introduces GPT-3, a 175-billion-parameter autoregressive language model, and demonstrates that it achieves strong performance on diverse NLP tasks through in-context few-shot learning without any task-specific fine-tuning. The model exhibits remarkable scaling properties where larger models dramatically improve…
Psychology & interventionsPlatforms, policy & society
Inoculating Against Fake News About COVID-19COVID-19 misinformation has proliferated rapidly on social media, undermining public health responses and vaccination uptake. Rather than relying on post-hoc fact-checking (which spreads slower than misinformation), the authors propose psychological inoculation—exposing people to weakened doses of misinformation techniques beforehand to…
Detection methodsSpread & networks
Mining Disinformation and Fake News: Concepts, Methods, and Recent AdvancementsThis comprehensive tutorial surveys the landscape of fake news and disinformation research across three dimensions: understanding user engagement in information disorder, techniques for detecting and mitigating false content, and emerging challenges like fake news literacy and neural generation. The authors emphasize weak social…
Datasets & evaluationDetection methods
Fighting an Infodemic: COVID-19 Fake News DatasetThe authors present a manually annotated dataset of 10,700 COVID-19 related posts and articles (52% real, 48% fake) collected from social media and fact-checking websites. They benchmark four machine learning baselines (Decision Tree, Logistic Regression, SVM, Gradient Boost), achieving 93.32% F1-score with SVM, and release both the…
Deepfakes & multimodalDetection methods
The Creation and Detection of Deepfakes: A SurveyComprehensive 38-page survey covering both creation and detection of deepfakes. Systematically reviews generative neural network architectures (GANs, autoencoders, CNNs, RNNs), technical approaches to reenactment, replacement, editing, and synthesis.
Bots & coordinated campaignsDatasets & evaluation
A Decade of Social Bot DetectionA comprehensive review of social bot detection research from 2010 to 2020, documenting the evolution from supervised individual-account detection to group-level approaches targeting coordinated inauthentic behavior. The paper traces the escalating "arms race" between bot developers and detection researchers, illustrates bots' documented…
Spread & networksDetection methods
Rumor Detection on Social Media with Bi-Directional Graph Convolutional NetworksProposes Bi-GCN, a graph convolutional network approach for rumor detection that models both top-down propagation patterns (how rumors spread from source) and bottom-up dispersion patterns (how rumors diffuse within communities). By capturing both directional characteristics jointly and incorporating source post features at each layer,…
Spread & networksDetection methods
What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media ContextThis paper predicts the political bias (left/center/right) and factuality (low/mixed/high) of news outlets by analyzing what articles they publish, who follows them on social media, and what Wikipedia says about them. The system achieves 85% accuracy on bias prediction by combining article text, YouTube video features, Twitter audience…
Deepfakes & multimodalFact-checking & verification
A Picture Paints a Thousand Lies? The Effects and Mechanisms of Multimodal Disinformation and Rebuttals Disseminated via Social MediaMultimodal disinformation (paired text and images) is perceived as more credible than text-only misinformation, but fact-checkers can overcome this effect. Importantly, the modality of fact-checks (visual or textual) matters less than their presence; fact-checks are more persuasive for people whose prior attitudes already oppose the…
Platforms, policy & societySpread & networks
Social media and vaccine hesitancyLarge-scale cross-national analysis finds that social media use to organize offline action predicts public vaccine safety skepticism, while foreign disinformation campaigns significantly reduce vaccination coverage year-over-year. A one-point increase on the five-point disinformation scale correlates with a two-percentage-point drop in…
Fact-checking & verificationPsychology & interventions
Fact-Checking: A Meta-Analysis of What Works and for WhomMeta-analysis of 30 studies on fact-checking effectiveness finds modest but significant positive effects (d = 0.29) on belief correction. However, effects are substantially moderated by motivated reasoning, political ideology, message design, and context: pro-attitudinal fact-checking works better than counter-attitudinal corrections,…
Deepfakes & multimodalPlatforms, policy & society
Deepfakes and Disinformation: Exploring the Impact of Synthetic Political Video on Deception, Uncertainty, and Trust in NewsExperimental study (N=2,005 UK respondents) testing how political deepfakes affect deception and trust in news. Deepfakes increased uncertainty about content, and that uncertainty mediated reduced trust in news on social media.
Spread & networksPlatforms, policy & society
Causes and consequences of mainstream media dissemination of fake news: literature review and synthesisWhile fake news websites have limited direct reach, mainstream media coverage is probably how most people encounter fake news stories. This synthesis identifies why mainstream outlets cover falsehoods (journalists' professional duties, news values, peer psychology, technical infrastructure) and explores how mainstream coverage amplifies…
Spread & networksPlatforms, policy & society
Online misinformation about climate changeComprehensive literature review examining climate change misinformation from multiple disciplinary angles. Defines misinformation vs. disinformation, identifies networks of actors (scientists, governments, industry, media) spreading false claims, examines how social media characteristics (homophily, echo chambers, algorithmic bias)…
Psychology & interventionsPlatforms, policy & society
Susceptibility to misinformation about COVID-19 around the worldAn international survey of 3,750 adults across five countries (UK, Ireland, USA, Spain, Mexico) measured susceptibility to COVID-19 misinformation and examined how it predicts public health behaviors. While majorities in each country did not find COVID-19 misinformation credible, higher susceptibility to misinformation was strongly…
Psychology & interventionsPlatforms, policy & society
Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge InterventionTwo pre-registered experiments with 1,700+ U.S. adults show that a simple accuracy nudge — asking people to rate the accuracy of an unrelated headline before the main task — nearly tripled their ability to discriminate true from false COVID-19 headlines when deciding what to share on social media. The intervention is scalable, requires…
Bots & coordinated campaignsPlatforms, policy & society
Troll Factories: Manufacturing Specialized Disinformation on TwitterLinvill and Warren analyze 9.04 million tweets from Russia's Internet Research Agency (IRA) spanning 2009–2018, identifying five specialized account categories—Right Troll, Left Troll, News Feed, Hashtag Gamer, and Fearmonger—each with distinct behavioral patterns, temporal deployment strategies, and communication styles. The authors…
Fact-checking & verificationPlatforms, policy & society
Fact-checking as risk communication: the multi-layered risk of misinformation in times of COVID-19COVID-19 misinformation should be viewed as a risk in its own right, not just a communication failure. Fact-checking efforts face three key challenges: defining misinformation differently across political subgroups, earning trust in an environment of low press credibility, and communicating amid genuine uncertainty.